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Intelligent Autonomous Systems 12: Volume 1 Proceedings of by José Miguel Vilca, Lounis Adouane, Youcef Mezouar (auth.),

By José Miguel Vilca, Lounis Adouane, Youcef Mezouar (auth.), Sukhan Lee, Hyungsuck Cho, Kwang-Joon Yoon, Jangmyung Lee (eds.)

Intelligent self sustaining structures are emerged as a key enabler for the production of a brand new paradigm of providers to humankind, as noticeable through the hot development of independent vehicles authorized for using in our streets, of unmanned aerial and underwater cars engaging in damaging initiatives on-site, and of area robots engaged in medical in addition to operational missions, to record just a couple of. This publication goals at serving the researchers and practitioners in similar fields with a well timed dissemination of the hot development on clever self sustaining structures, in response to a suite of papers provided on the 12th overseas convention on clever independent structures, held in Jeju, Korea, June 26-29, 2012. With the topic of “Intelligence and Autonomy for the carrier to Humankind, the convention has lined such varied parts as self reliant floor, aerial, and underwater cars, clever transportation platforms, personal/domestic carrier robots, expert provider robots for surgery/rehabilitation, rescue/security and house functions, and clever self sustaining platforms for production and healthcare. This quantity 1 comprises contributions dedicated to self sufficient flooring cars and cellular Manipulators, in addition to Unmanned Aerial and Underwater automobiles and Bio-inspired Robotics.

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Extra resources for Intelligent Autonomous Systems 12: Volume 1 Proceedings of the 12th International Conference IAS-12, held June 26-29, 2012, Jeju Island, Korea

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Our approach is inspired by the works done by Parhi and Singh [13–15] for neural network robot navigation. The third contribution of this work is that we develop a software application to carry out the proposed approach. The experimental results obtained through this application indicate feasibility of our approach in simulation robots. Fig. 1. Flowchart of proposed method In this section, we propose an approach to address the problem of extending neural network navigation algorithms for various robots and range sensors.

6), t is a given threshold. The largest value of k which satisfies Eq. (6) is determined as the optimal number of extraction to camera motion estimation. 4 Plane Reconstruction We employ the method in [7] for reconstructing planes. In [7], planes fitting to edge points are reconstructed if they satisfy visibility constraints. A triangle is generated by choosing arbitrary combination of three edge points. The planes which satisfy visibility constraint and fitting to edge points are chosen as correctly estimated planes.

Our approach extends the work done by Janglová [11] for determining the free-spaces by applying PCA Neural Network (PCNN). We study the problem of how current neural A Generalized Neural Network Approach to Mobile Robot Navigation 27 network navigation approaches are limited to one type of sensor and the kinematic constraints of a mobile robot. The second important contribution of this paper is to implement an algorithm to perform the navigation task using our interpretation of sensory data. Our approach is inspired by the works done by Parhi and Singh [13–15] for neural network robot navigation.

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